De La Salle University

About: De La Salle University is a education organization based out in Manila, Philippines. It is known for research contribution in the topics: Population & Computer science. The organization has 2951 authors who have published 4374 publications receiving 49567 citations. The organization is also known as: Pamantasang De La Salle.

X-Ray Microtomography of Mortars Exposed to Freezing-Thawing Action

Abstract: This paper presents our findings on the application of X-ray microtomography to characterize the internal structure of mortars that were exposed to freezing-thawing action. A microfocus X-ray CT (micro-CT) scanner was used for the nondestructive 3D imaging of internal air voids or cracks at a spatial resolution of the order of 10 microns. Four different types of mortar specimens (i.e., non-air-entrained and air-entrained Portland cement mortar, and non-air-entrained and air-entrained fly ash mortar) were scanned after being subjected to different numbers of freeze-thaw cycles. Coupled with image analysis, the void space obtained from micro-CT was characterized in three dimensions (3D) in terms of void fraction and air void size distribution, as well as, the crack width and tortuosity of the connected crack network. Results suggest that the initial air voids follow a lognormal distribution with the highest population of modal size around 30-50 μm, irrespective of the type of mortar. As the distributed air voids of non-air entrained mortars were relatively few in numbers, the fly ash mortar in particular was the least resistant against frost damage as shown by the formation of internal cracks that meander around the weaker paste-aggregate interface. Indications also suggest that these cracks are well connected and anisotropic in 3D.

Segregated targeting for multiple resource networks using decomposition algorithm

Abstract: A generalized decomposition technique is presented for determining optimal resource usage in segregated targeting problems with single quality index (e.g., concentration, temperature, etc.) through pinch analysis. The latter problems are concerned with determining minimal resource requirements of process networks characterized by the existence of multiple zones, each consisting of a set of demands and using a unique external resource. However, all the zones share a common set of internal sources. The decomposition algorithm allows the problem to be decomposed into a sequence of subproblems, each of which can in turn be solved using any established graphical or algebraic targeting methodology to determine the minimum requirement of respective resource. This article presents a rigorous mathematical proof of the decomposition algorithm, and then demonstrates its potential applications with case studies on carbon-constrained energy sector planning, interplant water integration, and emergy-based multisector fuel allocation. © 2009 American Institute of Chemical Engineers AIChE J, 2010